Obtaining more precise flavor percents

General Feedback
1

I noticed this information when I looked this flavor up on the other side:

Vanilla Custard v1 - Capella Flavors
You have this flavor

Bottle size: 13.00
ml Cost: 2.50
Weight in grams per ml: 1.0670
Flavor carrier: [ ] PG [ ] VG [x]Other
Preferred single flavor mix: ?.?? %

Flavoring MAY contain diacetyl - a flavoring used to create a butter flavor.
Contains Acetoin and Acetyl Propionyl
Materials Safety Data Sheet (MSDS) document

Manufacturer specified gravity: 1.067 g/ml

Percentages in recipes
Average mixing quantity: 4.3% (Median: 3%)
Minimum used quantity: 0%
Maximum used quantity: 75.8%

Single flavor recommendations: 141
Average quantity: 10.2% (Median: 10.0%)
Minimum used quantity: 0.5%
Maximum used quantity: 30.0%

Information I obtained from ANOTHER SOURCE.:

Vanilla Custard 12,50%
Averaged from: 8% 20% 11%18% 7% 11,00%

On this particular flavor the Average quantity: 10.2% (Median: 10.0%) is not too far off Dampfaromen-Prozentebut’s 12.5% I’m wondering how many statistical outliers are used in ELR’s average?
Sometimes data might look like 6, 4.5

image.png800Ă—600 31.9 KB

may actually be closer to 1.5, 4 once the outliers are removed.
This may be a good argument to have a check box for dripper/tanker, or possibly a way to view the data and manually deselect outliers hooligans and pranksters.

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2

Yep. That’s something I asked for sometime back. (MTL vs DL checkbox)

It would probably be a royal PITA to code for since everything has already been done (in the way the site aggregates data), not to mention, I can’t see how it would have a way to be implemented so that all current data is accurately reflected (without wiping the current data slate clean).

Personally, I use VC v1 at 6% as a SA/SF.

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3

Interesting manually deselect outliers hooligans and pranksters. I like it

4

RDA checkbox adds Root Means Squared to calculation

5

I’d love to see an “outlier corrected” line underneath the average/median line that calculates the average/median sans all the data above or below X (maybe 2.5 or 3?) standard deviations. You’d have the typical average/median we see currently with the outlier corrected average/median right below it. That may remove a lot of the stones that cause the averages to be higher than normal non-stone recipes and abnormally high or low usages out of the data for the second line.

6

Or it could just split the data right there.

and the hooligans and pranksters.
it might be cool to see even a bar scale plot of the data

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7

My personal usage (from my recipes and those I gathered that use VC V1) is:

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